Figma MCP Server with Chunking
A Model Context Protocol (MCP) server for interacting with the Figma API, featuring memory-efficient chunking and pagination capabilities for handling large Figma files.
Overview
This MCP server provides a robust interface to the Figma API with built-in memory management features. It's designed to handle large Figma files efficiently by breaking down operations into manageable chunks and implementing pagination where necessary.
Key Features
- Memory-aware processing with configurable limits
- Chunked data retrieval for large files
- Pagination support for all listing operations
- Node type filtering
- Progress tracking
- Configurable chunk sizes
- Resume capability for interrupted operations
- Debug logging
- Config file support
Installation
Installing via Smithery
To install Figma MCP Server with Chunking for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install @ArchimedesCrypto/figma-mcp-chunked --client claude
Manual Installation
# Clone the repository
git clone [repository-url]
cd figma-mcp-chunked
# Install dependencies
npm install
# Build the project
npm run build
Configuration
Environment Variables
FIGMA_ACCESS_TOKEN: Your Figma API access token
Config File
You can provide configuration via a JSON file using the --config flag:
{
"mcpServers": {
"figma": {
"env": {
"FIGMA_ACCESS_TOKEN": "your-access-token"
}
}
}
}
Usage:
node build/index.js --config=path/to/config.json
Tools
get_file_data (New)
Retrieves Figma file data with memory-efficient chunking and pagination.
{
"name": "get_file_data",
"arguments": {
"fileKey": "your-file-key",
"accessToken": "your-access-token",
"pageSize": 100, // Optional: nodes per chunk
"maxMemoryMB": 512, // Optional: memory limit
"nodeTypes": ["FRAME", "COMPONENT"], // Optional: filter by type
"cursor": "next-page-token", // Optional: resume from last position
"depth": 2 // Optional: traversal depth
}
}
Response:
{
"nodes": [...],
"memoryUsage": 256.5,
"nextCursor": "next-page-token",
"hasMore": true
}
list_files
Lists files with pagination support.
{
"name": "list_files",
"arguments": {
"project_id": "optional-project-id",
"team_id": "optional-team-id"
}
}
get_file_versions
Retrieves version history in chunks.
{
"name": "get_file_versions",
"arguments": {
"file_key": "your-file-key"
}
}
get_file_comments
Retrieves comments with pagination.
{
"name": "get_file_comments",
"arguments": {
"file_key": "your-file-key"
}
}
get_file_info
Retrieves file information with chunked node traversal.
{
"name": "get_file_info",
"arguments": {
"file_key": "your-file-key",
"depth": 2, // Optional: traversal depth
"node_id": "specific-node-id" // Optional: start from specific node
}
}
get_components
Retrieves components with chunking support.
{
"name": "get_components",
"arguments": {
"file_key": "your-file-key"
}
}
get_styles
Retrieves styles with chunking support.
{
"name": "get_styles",
"arguments": {
"file_key": "your-file-key"
}
}
get_file_nodes
Retrieves specific nodes with chunking support.
{
"name": "get_file_nodes",
"arguments": {
"file_key": "your-file-key",
"ids": ["node-id-1", "node-id-2"]
}
}
Memory Management
The server implements several strategies to manage memory efficiently:
Chunking Strategy
- Configurable chunk sizes via
pageSize - Memory usage monitoring
- Automatic chunk size adjustment based on memory pressure
- Progress tracking per chunk
- Resume capability using cursors
Best Practices
- Start with smaller chunk sizes (50-100 nodes) and adjust based on performance
- Monitor memory usage through the response metadata
- Use node type filtering when possible to reduce data load
- Implement pagination for large datasets
- Use the resume capability for very large files
Configuration Options
pageSize: Number of nodes per chunk (default: 100)maxMemoryMB: Maximum memory usage in MB (default: 512)nodeTypes: Filter specific node typesdepth: Control traversal depth for nested structures
Debug Logging
The server includes comprehensive debug logging:
// Debug log examples
[MCP Debug] Loading config from config.json
[MCP Debug] Access token found xxxxxxxx...
[MCP Debug] Request { tool: 'get_file_data', arguments: {...} }
[MCP Debug] Response size 2.5 MB
Error Handling
The server provides detailed error messages and suggestions:
// Memory limit error
"Response size too large. Try using a smaller depth value or specifying a node_id.""
// Invalid parameters
"Missing required parameters: fileKey and accessToken"
// API errors
"Figma API error: [detailed message]"
Troubleshooting
Common Issues
-
Memory Errors
- Reduce chunk size
- Use node type filtering
- Implement pagination
- Specify smaller depth values
-
Performance Issues
- Monitor memory usage
- Adjust chunk sizes
- Use appropriate node type filters
- Implement caching for frequently accessed data
-
API Limits
- Implement rate limiting
- Use pagination
- Cache responses when possible
Debug Mode
Enable debug logging for detailed information:
# Set debug environment variable
export DEBUG=true
Contributing
Contributions are welcome! Please read our contributing guidelines and submit pull requests to our repository.
License
This project is licensed under the MIT License - see the LICENSE file for details.